EFFECTS OF STRATEGIC MANAGEMENT DRIVERS ON THE PERFORMANCE ... · EFFECTS OF STRATEGIC MANAGEMENT DRIVERS ON THE ... examine the role of strategic management drivers on the performance

European Journal of Business and Innovation Research

Vol.2, No.1, pp. 93-119, March 2014

Published by European Centre for Research Training and Development UK (www.ea-journals.org)

93

EFFECTS OF STRATEGIC MANAGEMENT DRIVERS ON THE PERFORMANCE OF

HOTEL INDUSTRY IN KENYAN COAST

Uzel Jean Mzera Mutindi 1

PhD Candidate at JKUAT, MSA CBD, Kenya.

P. O. Box 666-80109, Mtwapa, Mombasa-Kenya

Prof. G.S. Namusonge, PhD 2

Full Professor, EPD JKUAT, Kenya.

Dr. J. Obwogi, PhD 3

Technical University of Mombasa, Kenya.

ABSTRACT: The purpose of this research was to examine the effect of strategic management

drivers on the performance of hotels in Kenyan coast. The general objective of the study was to

examine the role of strategic management drivers on the performance of hotels in Kenyan Coast.

The strategic management drivers selected for this study and which formed the specific objectives of

the study were: to find out the effect of customer relationship management (CRM) strategy, strategic

planning (SP), competitive positioning(CP), information communication technology(ICT) and

organizational learning(OL) on the performance of the hotel industry in Kenyan Coast. The study

adopted a mixed research approach which was both quantitative and qualitative using descriptive

survey. The population of the study was 180 managers of classified hotels in Kenya’s Coast. The

sampling technique that was used was stratified random sampling. Data collection methods involved

secondary and primary data. The instrument of study was a self administered questionnaire which

was used to collect data after it had been piloted for validity and reliability. The questionnaires were

administered through drop and pick method. An observation checklist was also used to account for

qualitative data Performance in the hotel industry was measured using both financial and non-

financial measures. In this study 123 hotels were extensively surveyed to ascertain their level of use

of strategic management drivers of hotels performance. The correlations between the five strategic

drivers were evaluated by using various statics tools and instruments. The findings revealed that

strategic management drivers had a positive influence on hotel performance. The overall results

indicated that there was a highly significant linear relationship between CRM strategy and hotel

performance and a moderately significant linear relationship between strategic planning (SP),

strategic competitive positioning (SCP) and hotel performance and a moderately low significant

relationship between Information communication technology (ICT), Organizational learning (OL)

and hotel performance. The study recognized strategic management drivers as some of the tools that

propel performance in the hotel industry. It recommended to hotels that they ought to embrace the

adoption of strategic management drivers. Hotels were also challenged to align their goals and

objectives to the stated strategic management drivers of performance in order to gain sustainable

competitive advantage (SCA). This research will go a long way in assisting hotels in identifying and

adopting strategic management drivers in order to enhance their performance. Enhanced

performance through the adoption of strategic management drivers will help hotels to create jobs,

improve the economy as well as making Kenyan hotels more competitive in the global hotel industry.

KEYWORDS: Hotel performance, Tourist Hotels, Strategic Management Drivers.

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INTRODUCTION

Kenya has been experiencing turbulent times with regard to its organizational practices in the

last two decades. This has resulted in generally low profits across the economy and this

picture is fairly well replicated in the Hotel Industry (Namusonge et. al., 2012). The decline

in world tourism has grossly affected hotel sales and posed a threat to hotel operators because

Kenyan hotels largely depend on the International Tourism Market (Oketch et. al., 2010).

Akama (2007) argued that in Kenya, there were declining incomes from agriculture and

manufacturing sectors. As a result, Kenya has turned her attention to tourism as an

intervention to the numerous economic problems. Kenya was considered all over the world

as a great tourist nation but recently the hotel industry was hit hard by the recent post-election

violence as well as terrorism attacks (Kuria et. al., 2012). Many hotels were closed and this

caused staff to be laid off. There were also a low bed occupancy capacity of 10-20% and the

situation was headed for worse if something was not done (Nzuve and Nyaega, 2011).

Similarly, Kenyan hotels have become more complex to manage because of the demands of

the dynamic business environment. Hotels were finding it difficult to meet the challenge of

customer demands as well as complicated service technologies and production processes.

Kamau (2008) stated that the tourism sector under which hotels is found in Kenya has been

facing numerous challenges which have posed a threat to their existence. These challenges

include competition, socio-cultural changes, technological changes and economic challenges.

Hotels like other businesses are turning to strategic management performance drivers so that

they can qualify for international recognition for standardization certificates, company of the

year awards and star rating as well as membership to professional bodies (Ongore and

Kobonyo, 2011). The Kenya Institute of Management (KIM) developed a model called the

Organizational Performance Index (OPI) which was a tool that drove organizations in Africa

towards excellent performance and competitiveness. The performance of organizations was

measured against global standards and benchmarks. The key parameters included systems

thinking, competitiveness, standards and continuous improvement.

The OPI model rated participating organizations using a scale of 1-10 using both its internal

and external processes. It used seven (7) global determinants which were leadership and

management, human resource, customer focus and marketing, financial aspects, Innovation

and technology, corporate social responsibility, environmental focus productivity and quality.

Organizations are then assessed according to specific indicators to their particular industry

(KLR, 2012). Hotels are therefore some of the organizations which must be assessed because

they play a key role in the economy of Kenya. This therefore poses another challenge on

hotels to improve their performance rating. Mukulu et.al., (2012) noted that performance

measurement was important for organization as a means of continuous improvement and also

as a means of determining whether or not an organization was achieving its objectives. The

traditional management approaches and models were no longer adequate to award a hotel a

sustainable competitive advantage (SCA) and technology becomes obsolete every so often

(Kingi et. al., 2013). This has posed a new challenge to managers in the hotel sector to

review the drivers of performance in their industry. This study therefore wished to bridge the

knowledge gap in the area of strategic management by re-examining the strategic

management drivers of performance in the hotel sector in Kenyan coast. This is because the



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research hypothesized that strategic management performance drivers could be the answer to

the current hotel dilemma.

LITERATURE REVIEW

Conceptual framework

In this study, the independent variables which were the conceptualized management drivers

of hotel performance included customer relationship management strategy (CRMS), strategic

planning (SP), strategic competitive positioning(SCP), information communication

technology(ICT) and organizational learning(OL). The dependent variable was hotel

performance (HP).

Independent Variables Dependent Variable

Figure: 2.2. Conceptual Framework

Customer Relationship Management (CRM) Strategy and Hotel Performance

Customer Relationship Management (CRM) is one of the strategic management concepts

which have changed the way businesses are carried out. Cooperative rather than competitive

approaches to businesses are now commonly embraced (Langerak and Verhoef, 2003).

Christian (2007) highlighted a positive relationship between customer relationship

management and organizational performance. This is because CRM is a comprehensive

strategy for acquiring, retaining and partnering with selected customers to improve quality for

the company and the customer (Sigala, 2005). Jain et. al., (2007) asserted that when CRM is

implemented in organizations it develops a series of functions, skills, processes and

technologies that help organizations to achieve long-term customer loyalty thereby improving

on their performance.

Customer Relationship

Management Strategy

Practices

Strategic Planning

Strategic Competitive

Positioning

Hotel

Performance

-

Organizational Learning

Information Communication

Technology

T



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Coltman (2007) contented that CRM is a core process in enhancing competitiveness and

performance. They further assert that CRM policies in the hotel sector must concentrate on

customer satisfaction, customer retention and customer quality. Teng et. al., (2007) also

suggested that CRM improves performance through its various processes because it enables

companies to evaluate their efficiency in serving customers. Hotels therefore have a duty to

identify customer needs in order to plan how to satisfy them (Zander and Zander, 2005).

Customer relationships are one of the most expensive assets a hotel can have because

satisfied customers are more likely to return to the hotels and also to recommend others

(Jones et. al., 2007). Uzel (2012) stated there was intense competition in today’s hotels

which requires managers to adopt strategic drivers of performance in order to improve hotel

services. Chen and Popovich (2003) stated that hotels that maintain long run performance are

the ones that are able to build customer loyalty and retention. Zablah et.al., (2004)

established that CRM brings benefits in terms of improved performance. This results from

acquiring new customers as well as sustaining customers for competitive advantage. CRM

also improves performance through reduction of the costs incurred in acquiring customers

and also the profitability that results from customer loyalty (Piccoli et.al., 2003). CRM

strategy is a customer centered rather than product centered interaction with customers which

adds value to the services offered in hotels to enhance the desired results. Minal and Kasim

(2009) stated that CRM improves hotels performance through engaging customers in long

term relationships in order to improve profits in the hotel industry. Customer Relationship

Management Strategy if applied will attract new customers in the hotel industry which was

facing a lot of competition and required that they differentiate their customers (Piccoli et.al.,

2003). Hotels like other organizations needed to assess users satisfaction levels towards

their service so that they could use the feedback to make positive adjustments to their

products and services. Iravo et. al., (2013) stated that dissatisfied customers were disloyal to

the organization and talked about their bad experience to other customers. In this study CRM

was viewed as a customer strategy for retaining customer loyalty and improving hotels

performance.

Strategic planning and hotel performance The history of strategic planning dated back to long-range planning (Cappelli, 2005).

Strategic planning was therefore a proactive alternative to long-range planning which was

found to be obsolete because it was not increasing firm’s true value. Strategic Planning is a

core task of senior management which involves fourteen (14) processes (Armstrong, 2010).

These processes are designing objectives, planning strategy, establishing goals, developing

company philosophy, policies, procedures, organization structures, establishing personnel and

facilities, capital, establishing standards, programs and operational plans and

institutionalization, evaluation and control. Pearce and Robinson (2008) viewed Strategic

Planning as an organizational process that is vision driven and that aims at developing the

future value of an organization. Dan (2009) stated that Strategic Planning process involves

the implementation of strategy in an organization which should be managed through a

sequence of steps. These steps include setting of objectives, analysis of environmental trends

& capabilities, evaluation of the available options and planning, implementation,

operationalization and institutionalization of strategy.



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Barney and Hesterly (2006) were of the view that the process of strategic planning was

designed well such that it met the specific needs of the organization. The strategic

management planning process involved the mission and vision of the organization,

environmental analysis, selection of objectives and analyzing strategic choices (Porter, 2004).

There were no any best way of conducting the process of strategic planning in an

organization and therefore strategies should be formulated explicitly and implicitly (Johnson

and Scholes, 2003). Hotels have acknowledged the importance of strategic planning just like

other organizations. This is because strategic planning helps organizations to clearly identify

and prioritize their objectives, and targets. Strategic planning however has to be done under

a conducive strategic planning environment which has the appropriate structures for proper

coordination and cooperation (Dobini, 2003). Manager’s perception was also very important

to the strategic planning process because they are the initiators as well as the implementers of

the plans (Balogun, 2003). The concept of strategic planning has been widely adopted by

hotels but its dimensions, roles and impact to the performance of the overall hotel

management was still disputable. Creating a winning strategy is not a one-time event

because a good strategy today might not be successful tomorrow. Changes in the business

environment are leading to new and greater demands on strategic planning systems. Jehad

and Adel (2013) asserted that there were several planning systems used by hotels in order to

manage change and these systems have evolved in order to cope with the continuously

changing environment. Strategic plans can help hotels communicate their goals, strategies

and operational tasks to internal and external stakeholders (Galbreath, 2010). Higher

planning formality is beneficial for firms that operate in highly competitive environments like

hotels and this may assist them to meet competitive threats more systematically (Law and

Jogaratnam, 2005). A hotel could adopt strategies in both the internal and external

environment. The internal environment included the physical and social factors within the

boundaries of the hotels or specific decision units that are taken directly into consideration in

the decision-making behaviour of individuals in those systems (Richard et. al., 2009).

Internal environment also can refer to the amount of attention devoted to a hotel’s recent

history and current situation, its past performance and an analysis of its strengths and

weaknesses. On the other hand, external orientation involves the ability to obtain reliable

research information in order to learn about external environmental opportunities and threats

(Dincer et.al., 2006). These opportunities and threats refer to those relevant factors outside

the boundaries of the hotel or specific decision units that are taken directly into consideration

(Pinea and Phillips, 2005). Johnson and Scholes (2003) stated that for a formal planning

process to assist in strategy development, it must include mechanisms to embrace proper

customer services, efficiency of operating processes, alternating and retaining high quality

employees, and analysis of financial strengths and weaknesses. The external orientation will

create analysis of investment opportunities, analysis of competition and reforming market

research.

Wheelen and Hunger (2008) concluded that strategic planning attempts to look ahead to

where a firm wants to be in future together with the budget to get there. In the recent times,

the hotel industry has identified the importance of strategic planning by defining the mission

of their businesses so that they are better able to give themselves a direction to focus their

activities. Strategic planning helps managers to identify a clear-cut concept of their hotels

and as a result of this make it possible to formulate plans and activities that will bring them



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close to their goals (Pearce and Robinson, 2008). Kenyan hotel managers operate in a world

that is ever changing and nothing is static whether in technology, politics or society. They

therefore have no choice but to come up with strategic planning as a tool for the future

prospects of their hotels.

Strategic Competitive Positioning and hotel performance

Competitive advantage (CA) has been defined differently by different authors but all of them

agree that it related to strategy formulation and implementation in organizations (Porter,

2009). Hotels that desire to perform must select strategies that gave them a competitive

advantage over their competitors based on their core competencies (Porter, 2004).

Organizations can do strategic analysis to achieve competitive advantage using tools such as

Strengths Weaknesses Opportunities Threats (SWOT) Analysis, Porter’s five forces Model

and the RBT of the firm (Harrison, 2003). Strengths, Weaknesses, Opportunities, and

Threats analysis aims at matching an organizations internal strengths and weaknesses with its

external opportunities and threats. Porters Five Forces Model determines the firms’ abilities

to position and compete in the industry. Mibei (2007) also proposed three generic strategies

which could help organizations to cope with competitive forces and these include focus, cost

leadership and differentiations. Previous RBT research has provided evidence that the

analysis of a firm’s internal resources helps firms to realize their competencies and

capabilities which are inimitable by their competitors (Wang and Ahmed, 2007).

Lo (2012) stated that firm’s resources include assets, capabilities, organizational processes

and knowledge that help firms to implement strategies that improve performance. Other

researchers refer to these resources as core competencies and capabilities that could generate

competitive advantage (Barney and Peteref, 2003). A few hospitality researchers have stated

core competencies of hospitality organizations to be processes, skills and assets that influence

organizations to achieve competitive advantage (Barney, 2001b). Sources that have also been

mentioned to contribute to core competencies are location, brand, facilities, employee,

customer loyalties, market coverage, market share, service quality, technology, leadership,

systems and procedures and organizational culture (Peteraf and Bergen, 2003). Hotels are

dynamic organizations which are affected by diverse variables hence the application of

Competitive advantage will help them to sustain exemplary performance. Richard and

Marilyn (2006) argued that the essence of business strategy formulation is coping with

competition. Moullin (2007) also suggested that business strategy was all about

competitiveness because the main purpose of strategy adoption was to enable a hotel gain a

sustainable edge over its competitors. Tavitiyaman et. al., (2011) stated that hotel’s

strategies consists of competitive moves and business approaches that managers employ to

attract and please customers, compete successfully, grow the business, conduct operations

and achieve targeted objectives. A hotel achieves sustainable competitive advantage when an

attractive number of customers prefer its services over the offerings of competitors and when

the basis of this preference is durable (Sabah et. al., 2012). Businesses will only result in

superior performance when the appropriate strategic management drivers of performance are

adopted. The management of these key success factors results in superior value. Hotels can

take advantage of their overall products and services to come up with services which are

superior to their competitors. Lo (2012) observed that porters’ generic strategy can create

competitive advantage for a firm through the adoption of differentiation and cost-leadership.



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These strategies give a firm a better chance of outperforming other firms in a homogeneous

industry. Porter (2004) described porter’s five forces as the threat of new entrants, threat of

substitutes, bargaining power of suppliers and buyers and the intensity of rivalry. Firms in a

particular industry need to adopt these five drivers in order to improve their performance.

Porter (2009) stated that for a firm to achieve high performance it has to achieve one of the

basic competitive advantages which are lower cost and differentiation. He further suggests

that a firm which does not adopt any one of these strategies is geared towards failure.

Differentiation can take different forms such as various marketing strategies, better product

image, better market awareness, low prices, higher product quality and better customer

service or availability of goods (Lo, 2012). Strategic management scholars have been asking

key questions regarding why firms perform better than others (Peng, 2002). These scholars

claimed that a firm superior’s performance was influenced by many factors (Davidson, 2005).

Differentiation helped firms to build customer loyalty through offering unique products or

services (Allen and Helms, 2006).

Firms that adopted differentiation could charge higher prices based on their costs, channels of

distribution and quality (Akan et. al., 2006). Differentiation strategies could be classified

into market and product strategies. In product-innovation, firms outperformed their

competitors by increased creativity, quality, efficiency and innovations among others. Lo

(2012) states that there are few examples of differentiation in hotel industry such as designer

hotels and Boutique hotels. Marketing differentiation involves the use of marketing

practices for hotels to differentiate themselves which include market segmentation, branding,

promotions, pricing and advertising (Akan et. al., 2006). A hotel could gain competitive

advantage by adopting a low cost strategy such as mass production, technology adoption,

achieving economies of scale and access to raw materials (Campbell-Hunt, 2000). A cost-

leadership strategy can improve the performance of hotels by giving them distinctive

competencies in the management of materials and also in the production process.

Information Communication Technology (ICT) and hotel performance

Sirawit et. al., (2011) observed that the use of ICT is an integral part of hotels because it

increases hotel performance in various ways. Firstly, the use of ICT improves managerial

activities and leads to better organizational performance. ICT has therefore been recognized

as one of the drivers of hotel performance because hotels globally have to use ICT for all

their processes (Ham et. al., 2005). ICT has been widely used in hospitality industry to

eliminate the gap between purchase and service experience (Law and Jogaratnam, 2005).

This is because hospitality is a service which may not be experienced in advance because

decisions are made away from guest experiences. Innovation entails addition of new

technical knowledge to production of goods and services.

Technological innovation includes the development of new business methods to achieve

desired objectives. ICT led to high organizational performance which was characterized by

high financial income, continuous sustainable innovations, satisfied customers and a

motivated human resource (Epstein, 2004). Sabri et. al., (2004) in his study established a

positive relationship between ICT and the performance of firms. ICT positively influences

employee performance because it is the human capital that spearheads innovations. All types

of ICT were totally dependent on the human resource of the organization that designed, run



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and reviewed the programs (Zaheer et. al., 2011). Wong et. al., (2007) confirmed a positive

relationship between innovation and organizational performance and therefore when an

organization achieves competence in making a certain product; it can add value to the product

by investing in the latest and modern technology. The Resource Based Theory of the firm

explains the role of ICT and performance by assuming that distinctive competencies are

relatively stable overtime and are heterogeneously shared across firms (Denson, 2008). ICT

has been cited as one of the valuable resources and sources of competitive advantage which

influence organizational performance. Information Communication Technology involves the

introduction of modern ideas within an organization which is one of the driving forces of

performance in hotels (GoK, 2007). Cagna (2007) proposed ICT as one of the ways for the

survival of organizations today. Shimpton et. al., (2006) stated that ICT can be sustained by

involving human resources to manage, create, transfer and implement knowledge.

The adoption of ICT has been widely supported by literature in the hotel industry which

identifies it as a strategic driver to organizational performance (Sharma and Upneja, 2005).

Law and Jogaratnam (2005) supported the use of IT for operational purposes by stating that

firm and location related factors are among the key issues that influence adoption of ICT in

hotels. Lau et. al., (2005) highlighted that the use of ICT in hotels was becoming a

complicated affair because little attention had been given to the integration of ICT to key

strategic management drivers (Segnupta et. al., 2006). Barkhi and Daghfous (2009) stated

that competition among hotels is a major catalyst for the need for innovation in technology

because of the dynamic nature of today’s organizations. Hotels just like other organizations

have been forced to look for new sources of competitive advantage one of which was ICT

(Raisinghani, 2005). Barkhi and Daghfous (2004) highlighted the readiness of hotels to

adopt ICT and best practices and stated that current ICT infrastructure in hotels was enough

to support adoption of best practices and improve the hotels performance.

Organizational learning and hotel performance

Njuguna (2009) stated that organizational learning is a fundamental source of competitive

advantage in organizations. He further stated that it helps firms to obtain sustainable

competitive advantage through the development of its unique learning knowledge resources

and capabilities. Hotels like many other businesses are facing a lot of competitive challenges

arising from the dynamism and complexity of the business environment (DeNisi et. al.,

2003). This state of affairs has propelled academicians and hotel practitioners to study

distinctive firm competencies that add value to the final consumer. Hotels just like other

organizations have to encourage their employees to continually learn new skills and to be

innovative in order to achieve their strategic alternatives (GoK, 2003). Winter (2003)

proposed four stages of organizational learning which were knowledge acquisition,

distribution, application and translation into organizational resources such as procedures,

systems and databases which can be used for leveraging the firm. DeNisi (2003) highlighted

that when a firm obtains individual level resources such as knowledge or human capital it has

to leverage these resources to organizational capital so that the whole organization can

benefit. Intellectual capital is therefore a key determinant of value creation for

organizations. Intellectual capital can be divided into organizational capital, social capital

and human capital. Armstrong (2010) highlighted that through organizational learning a firm

can develop unique intellectual capital that other firms cannot imitate.Organizational learning



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helps people in the organization to question themselves about organizational systems and

challenges and endeavor to seek for solutions (Murray and Donegan, 2003).

Hotel Performance.

Performance is a complex and dynamic concept which has been conceptualized in two ways

namely the drivers of performance and the results of performance (Neely 2005).

Organizational performance is concerned with the overall productivity in an organization in

terms of stock turnover, customers, profitability and market share. Competition in the global

economy has intensified the importance of identifying the drivers of sustainable performance.

The search for such drivers is no longer restricted to tangible factors but has expanded to

include intangibles. Performance may be measured by both quantitative and qualitative

methods. Ittner and Larcker (2003) stated that non-financial measures are better performance

indicators in the service industry than financial measures. This is because non-financial

measures are better measures of value and motivation which complement short-run financial

figures as indicators of long-term goals.

Performance is regarded as an output which is aligned to objectives or simply profitability

and is explained in terms of expected behavioural output and also results. Odhuon et. al.,

(2010) asserted that the only worthy performance measure is financial performance because

of its value to shareholders, executives and the market. This measure is an indicator of

organizational success and sustainability because it is the reason for the existence of firms.

The financial success of an organization is a measure of a firm’s performance because it

depicts the ability of an organization to operate above all its costs. Ittner and Larcker (2003)

claimed that a firm’s performance should not be measured by financial performance but also

operational and market indicators. Financial Performance for this research was measured

using profitability and growth in sales while non-financial indicators will be service quality

and customer satisfaction. Non-financial measures have been deemed to be more effective in

motivating managerial performance because they are more reflective of the overall corporate

strategy (Banker et. al. 2005). The hotel industry is a service sector with inseparable

products which demand for different methods of measurement (Bowie and Buttle, 2004).

This means that a hotel is obliged to not only deliver services and products but also to

increase customer satisfaction by providing quality and hence improvement of profits

(Ramsaran-Powdar, 2007). Previous studies on hotel industry have indicated that customer

satisfaction influences hotels competitive advantage and performance (Barsky and Nash,

2003).

RESEARCH METHODOLOGY

Research Design

The study adopted a mixed research design which included qualitative and quantitative

research to establish the associations among the key study variables, to verify results and

enable greater accuracy in measurement. Qualitative data was collected by use of direct

observation and face to face interviews to get the opinions, perceptions and experiences of

the managers in the hospitality industry. The advantage of using both designs is that they

complemented each other and there is also a possibility of getting more valid results through



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an address of the inefficiencies of either design (Ramchander, 2004). A cross-sectional

survey design was the specific design that was used. This design has been used by several

authors in their research on the hospitality industry in Kenya (Fwaya et. al., 2012; Wadongo

et. al., 2010; Odhuno et. al., 2010; Kingi, 2013). The advantage of this design over others

was that data was collected less expensively and within a short time. The characteristics of

variables did not change much in the short period of data collection. The purpose of the

cross-sectional design was to establish relationships between drivers and the results of

performance for hotels in Kenyan Coast.

Sampling technique and sample size

Stratified sampling was used to select the hotels for each category for the study, that is, 1 to 5

star hotels. The hotels were obtained from the classification list. The classified hotels were

selected for the study because they have clear and consistent organizational structures which

implied that the results could be generalized without a lot of errors. Kothari (2012) noted

that stratified sampling was used when a population from which a sample was drawn did not

constitute a homogeneous group. This was the case with the categorization of hotels into

different stars. The method also involved dividing the population into a series of relevant

strata which implied that the sample was likely to be more representative (Saunders et. al.,

2009).

Sample Size

To compile the hotel sample size, 123 hotels were selected out of a total population of 180

using Saunders formula for sample size determination. The hotels in each stratum which were

selected for the sample of study were obtained using Neymans (1934) formula.

Data analysis and presentation

Cooper and Schindler (2003) highlighted data analysis as inspection, cleaning, transforming

and modelling data in order to highlight useful information to draw conclusions and to

support decision making. The questionnaires were edited for completeness and consistency

to ensure that respondents completed them as required. The collected data was tested for

normality using Kolmogorrov-Smirrov (KJ) one sample test and Kurtosis. Kurtosis

measured the flatness or peakness of data with a peaked distribution being positive and a flat

one being negative. A normal distribution should have a kurtosis of 0. The collected data

was coded and entered into SPSS to create a data sheet that was used for analysis. The

variables that were measured were defined and labelled. The responses were coded with

numbers including the open ended questions. After data was collected it was screened and

cleaned to find out whether there were errors that could be corrected. Data was analyzed

using quantitative and qualitative techniques. Descriptive statistics were used to describe the

characteristics of collected data. Pearson’s Correlation, Analysis of variance (ANOVA)

and Multiple Regression Analysis using Logit model were used to establish the relationships

among the study variables. The entire hypothesis was tested at 95% confidence level.

Responses were assigned numerical values which were consistent with numerical codes.

Quantitative Analysis

The data analysis processes for quantitative items was done using the statistical package for

social sciences (SPSS) version 20. Qualitative data was measured through correlation



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coefficient to establish initial relationships between variables. Karl Pearson’s Zero Order

coefficient of correlation test was used to compare observed data with the data the

researcher had hypothesized (Kothari, 2012). The model used for this analysis was multiple

regression analysis which was as follows:

Y= βo+ β1X1 + β2 X2+ β3 X3 a+β4 X4 + β5 X5 + ε

Where:-

Y = Dependent variable (Hotel performance)

X1 = Independent variable #1(Customer relationship management

strategy)

X2 = Independent variable #2(Strategic planning)

X3 = Independent variable #3(Strategic competitive positioning)

X4 = Independent variable #4(ICT)

X5 = Independent variable #5(Organizational Learning)

β1 –β5 = Regression coefficient for each Independent variable

ε = Random or Stochastic Term.

Hypothesis was tested at 95% confidence level (α = 0.05). A two tailed test was carried out.

DATA ANALYSIS AND DISCUSSION

Test of the hypotheses

The study was based on the premise that strategic management drivers (independent variable)

influence hotel performance (dependent variable). As a result of this, five null hypotheses

were constructed to guide the study as highlighted in the conceptual framework. In order to

establish the statistical significance of the respective hypothesis, simple regression analysis

was used to statistically test the hypotheses as presented in the discussions below. The

hypothesis was tested at 95 percent confidence level (α ═ 0.05).

Effect of Customer relationship management on Organizational performance

In order to assess the influence of Customer relationship management on Organizational

performance, the study had set the following null hypothesis; H01There is no relationship

between Customer relationship management strategy and the performance of hotels in

Kenyan Coast. The aggregate mean score of CRM measures (Independent variable) were

regressed on the aggregate mean score of the organizational performance measures

(dependent variable) and the relevant results presented in table 4.

Table 4 Regression Results of CRM against Organizational Performance

Goodness of fit analysis

N R

R

Square

Adjusted R

Square Std. Error of the Estimate

98 0.452 0.348 0.527 0.328

Predictors: (Constant) Aggregate mean score of Customer Relationship Management

Overall significance: ANOVA (F-test)

Sum of

Squares

Degree of

Freedom

Mean

Square F Significance(p-value)



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Source: Research Data

From the Table 4, the regression results reveal statistically significant positive linear

relationship between customer relations management and organizational performance (β=

.652, p-value = 0.000). The hypothesis criteria was that the null hypothesis H0 should be

rejected if β ≠ 0 and p-value ≤ α otherwise fail to reject H0 if the p-value > α. From the above

regression results, p-value = 0.000 ≤ α, the study therefore rejects the null hypothesis since

β≠0 and p-value < α and conclude that customer relationship management significantly

affected organizational performance. The regression results also shows that CRM had

moderate explanatory power on organizational performance in that it accounted for 34.8

percent of its variability (R square = 0.348). Arising from the results in Table 4.6, the

following simple regression equation that may be used to estimate organizational

performance of hotels in Kenyan coast given level of customer relationship management can

be stated as follows;

OP =1.347+ 0.652CRM+ ε

Where:

1.347= y-intercept constant,

OP= is the Organizational Performance

0.652 = an estimate of the expected increase in hotel performance corresponding to an

increase in customer relations management).

CRM = Customer Relations Management

ε = the error term- random variation due to other unmeasured factors.

Effect of strategic planning on the performance of hotels in Kenyan Coast. In order to assess the influence of strategic planning on organizational performance, the study

had formulated the following null hypothesis;

H02 There is no relationship between strategic planning and the performance of hotels

in Kenyan Coast.

The aggregate mean score of strategic planning measures (Independent variable) were


(dependent variable) and the relevant research findings are presented in Table.4.2. From the

Table 4.2, the regression results reveal statistically significant positive linear relationship

Regression 2.208 4 2.208 34.018 0.000

Residual 1.430 94 0.134

Total 3.638 98

Predictors: (Constant), Aggregate mean score of Customer Relations Management

Dependent Variable: Aggregate mean score of Organizational Performance

Individual significance (T-test)

Unstandardized

Coefficients

Standardized

Coefficients

T

Significance(p-

value)

B Std. Error Beta (β)

(Constant) 1.347 2.087 3.412 0.040

Means of CRM 0.652 0.184 0.734 2.089 0.000

Dependent Variable: Aggregate mean score of Organizational Performance

Lever of significance, α = 0.05



Vol.2, No.1, pp. 93-119, March 2014


105

between strategic planning and organizational performance (β = 0.542, p-value = 0.028). The

hypothesis criteria was that the null hypothesis H0 should be rejected if β ≠ 0 and p-value ≤ α

otherwise fail to reject H0 if the p-value > α. From the above regression results, β ≠ 0 and p-

value < α, the study therefore rejects the null hypothesis. The regression results also shows

that strategic planning had moderate explanatory power on organizational performance in that

it accounted for 36.4 percent of its variability (R square = 0.364).

Table 4.2 Regresion results of Strategic Planning against Performance

Goodness Fit Analysis

Predictor Variable: Aggregate Mean Score of Strategic Planning

Overall significance, ANOVA (F-test)

Sum of Squares

Degree of

Freedom Mean Square F

Sign. p-

value

Regression 1.248 1 0.408 1.0716 0.028

Residual 2.086 97 0.342

Total 3.334 98

Predictors: (Constant): Aggregate Mean Score of Strategic Planning

Dependant Variable: Aggregate Mean Score of Organizational Performance


Unstandardized

Coefficients

Standardized

Coefficients

T

Sign.

p-

value B Std. Error Beta (β)

(Constant) 2.681 1.01 1.098 1.688

Strategic Planning 0.542 0.451 0.464 0.08 0.028

Dependant Variable: Aggregate Mean Score of Organizational Performance


N R R squared Adjusted R2

Estimate

std error

98 0.340 0.364 0.104 0.736

Source: Research data, 2013

Arising from the results in Table 4.3, the following simple regression equation that may be

used to estimate organizational performance of hotels in Kenyan coast given level of

customer relationship management can be stated as follows;

OP =2.681+ 0.542SP+ ε

Where:



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2.681 is the y-intercept; constant,

OP is the Organizational performance

0.542= an estimate of the expected increase in organizational performance corresponding to

an increase in use of strategic planning).

SP is strategic planning

ε is the error term- random variation due to other unmeasured factors.

Effect of Strategic Competitive Positioning on Organizational Performance

To assess the effect of strategic competitive positioning on organizational performance of

hotels in Kenyan Coast, the study had set the following null hypothesis:

H03 There is no relationship between strategic competitive positioning and the

performance of hotels in Kenyan Coast.

The aggregate mean score of strategic competitive positioning measures (Independent

variable) were regressed on the aggregate mean score of the organizational performance

measures (dependent variable) and the relevant research findings are presented in Table.4.3.

From the Table 4.3, the regression results reveal statistically significant positive linear

relationship between strategic competitive positioning and organizational performance (β =

0.492, p-value = 0.008). The hypothesis criteria was that the null hypothesis H0 should be

rejected if β ≠ 0 and p-value ≤ α otherwise fail to reject H0 if the p-value > α. From the above

regression results, β ≠ 0 and p-value < α, the study therefore rejects the null hypothesis. The

regression results also shows that strategic competitive positioning had explanatory power on

organizational performance in that it accounted for 49.2 percent of its variability (R square =

0.492).

Table 4.3 Results of Regression of strategic competitive positioning against

organizational Performance

Source: Research data

The regression results in table 4.3 shows that on overall significance, there is a slightly

statistical positive linear relationship between strategic competitive positioning and hotel

performance (β=0.267) and the relationship is statistically significant because the p-value is

less than the set value of α (p – value = 0.008). The hypothesis test criterion was that the null

hypothesis which is H0 should be rejected if β ≠ 0 and p-value < α otherwise fail to reject if β

= 0 and p-value > α. From the regression results, β = 0.267 and p – value = 0.008, the study

therefore rejects the null hypothesis and concludes that there is significant effect of strategic

competitive positioning on organizational performance. The regression results also show that

18.8 percent of hotel performance can be explained by strategic competitive positioning (R

square = 0.188). Arising from the research results in Table 4.8, a simple regression equation

that may be used to estimate hotel performance in Kenyan coast given their existing strategic

competitive positioning can be stated as follows;.

OP = 1.830+ 0.267SCP + ε

Where:

OP is the Organizational Performance

1.830 is the constant intercept of the term (α = 1.830), or the slope coefficient,

0.492 is the beta or the slope coefficient, (estimates of the expected increase in organizational

performance corresponding to an increase in use of strategic competitive positioning).

SCP is Strategic Competitive Positioning



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107


Effect of ICT on performance of hotels in Kenyan coast

To assess the effect of ICT on the organizational performance of hotels in the Kenyan coast,

the study formulated the following null hypothesis;

H04 There is no relationship between adoption of ICT and the performance of hotels in

Kenyan Coast.

The aggregate mean score of ICT (Independent variable) were regressed on the aggregate

mean score of the organizational performance measures (dependent variable) and the relevant

research findings are presented in Table.4.4 .From the Table 4.4, the regression results reveal

statistically significant positive linear relationship between ITC and organizational

performance (β = 0.442, p-value = 0.004). The hypothesis criteria was that the null

hypothesis H0 should be rejected if β ≠ 0 and p-value ≤ α otherwise fail to reject H0 if the p-

value > α. From the above regression results, β ≠ 0 and p-value < α, the study therefore

rejects the null hypothesis. The regression results also shows that strategic competitive

positioning had explanatory power on organizational performance in that it accounted for

44.2 percent of its variability (R square = 0.442).

Table 4.4 Regresion results of ICT against hotel performance

Goodness of fit analysis

N R R Square Adjusted R Square Std. Error of the Estimate

98 0.291 0.188 0.143 0.572

Dependent Variable: Aggregate Mean Score of Strategic Competitive Positioning

Overall significance ANOVA (F-test)

Sum of Squares Degree of Freedom Mean Square F

Significance.

(P-value)

Regression 1.362 1 0.636 1.621 0.008

Residual 5.351 97 0.334

Total 6.713 98

Predictors: (Constant): Strategic Competitive Positioning

Dependent Variable: Aggregate mean score of Performance


(Constant)

Unstandardized Coefficients

Standardized

Coefficients T

Significance

(P-value).

B Std. Error Beta

1.830 0.549 2.334 0.003

Strategic Competitive

Positioning 0.492 0.212 0.367 1.379 0.008





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Source: Research data

From the Table 4.4, the regression results reveal that ICT had overall significant

positive relationship with the performance of the hotels (β = 0.442, p-value = 0.004). Hence

the study therefore rejects the null hypothesis since β ≠ 0 and p-value ≤ α and concludes that

ICT affected performance of hotels in Kenyan coast. The regression results also shows that

46.4 percent of the hotel performance can be explained by ICT (R square = 0.442). Arising

from the research results in Table 4.4, a simple regression equation that may be used to

estimate hotels performance in Kenyan coast given its existing ICT level can be stated as

follows;

OP = 2.681+ 0.442ICT+ ε

Where:

2.681 = y-intercept constant,

OP = Organizational Performance

0.442= an estimate of the expected increase in organizational performance corresponding to

an increase in use of ICT.

ICT is Information Communication Technology


(Constant)

Unstandardized Coefficients

Standardized

Coefficients

T

Sign. p-

value


2.681 1.01 1.098 1.688

ICT 0.442 0.451 0.464 0.08 0.004

Goodness Fit Analysis

N R R squared Adjusted R2 Estimate std error

98 0.383 0.264 0.104 0.736

Predictors: (Constant): Aggregate Mean Score of ICT.


Predictors: (Constant): Aggregate Mean Score of ICT.



Dependent Variable: Aggregate mean score of Performance Lever of significance, α = 0.05



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Effect of Organizational learning on performance of hotels in Kenyan coast To assess the effect of organizational learning on the organizational performance of hotels in

the Kenyan coast, the study formulated the following null hypothesis;

H05 There is no effect of organizational learning on the performance of hotels in Kenyan

Coast.

The aggregate mean score of organizational learning measures (Independent variable) were


(dependent variable) and the relevant research findings are presented in Table.4.5. From the

Table 4.5, the regression results reveal statistically significant positive linear relationship

between strategic organizational learning and organizational performance (β = 0.342, p-value

= 0.014). The hypothesis criteria was that the null hypothesis H0 should be rejected if β ≠ 0

and p-value ≤ α otherwise fail to reject H0 if the p-value > α. From the above regression

results, β ≠ 0 and p-value < α, the study therefore rejects the null hypothesis. The regression

results also shows that organizational learning had moderate explanatory power on

organizational performance in that it accounted for 34.2 percent of its variability (R square =

0.342).

Table 4.5 Regresion results of Organizational learning against Performance Goodness Fit Analysis

Predictors: (Constant): Aggregate mean score of Organizational Learning


Predictors: (Constant): Aggregate mean score of Organizational learning



Unstandardized Coefficients Standardized Coefficients

T

Sign. p-

value


(Constant) 2.681 1.01 1.098 1.688

N R R- squared Adjusted R2 Estimate std error

98 0.243 0.342 0.104 0.736

Sum of Squares Degree of Freedom Mean Square F

Sign. p-

value

Regression 0.248 1 0.408 1.0716 0.014

Residual 1.086 97 0.342

Total 1.334 98



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110

Vertical

diversification 0.342 0.451 0.464 0.08 0.014

Dependent Variable: Aggregate mean score of Performance Lever of significance, α = 0.05

Source: Research data, 2014

From the Table 4.5, the regression results reveal that organizational learning had overall

statistically significant positive linear relationship with the performance of the hotels (β =

0.342, p-value = 0.014). Hence the study therefore rejects the null hypothesis since β ≠ 0

and p-value < α and concludes that organizational learning affected performance of hotels in

Kenyan coast. The regression results also shows that 26.4 percent of the hotel performance

can be explained by organizational learning (R square = 0.264). Arising from the research

results in Table 4.5, a simple regression equation that may be used to estimate hotels

performance in Kenyan coast given its existing organizational learning level can be stated as

follows;

OP = 2.681+ 0.342OL+ ε

Where:

2.681 = y-intercept constant,

OP = Organizational Performance


increase in use of customer relations management).

OL = Organizational learning


In order to determine the effect of strategic management drivers on the organizational

performance of hotels in the Kenyan coast, the researcher conducted a multi-regression

analysis and individual strategic management drivers measures were regressed against the

aggregate mean score of organizational performance and the results are shown in Table 4.6

below.

Table 4.6: Regression Results of strategic Management Drivers against Performance

Goodness of fit Analysis

N R (Beta) R Square Adjusted R Square Std. Error of the Estimate

98 0.641 0.511 0.316 0.040

Predictors: (Constant): Strategic Management Drivers

Overall significance ANOVA (F-test)

Sum of

Squares

Degrees of

Freedom Mean Square F

Significance

(p-value)

Regression 1.081 5 1.018 2.162 0.008

Residual 2.230 93 0.112

Total 3.311 98

Predictors: (Constant), Strategic management drivers.

Dependent Variable: Organizational performance.



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111


Unstandardized

Coefficients

Standardized

Coefficients

T

Significance

(p-value) Beta Std. Error (r)

(Constant) 2.347 1.299 2.412 0.042

CRM 0.540 0.187 0.381 2.421 0.037

Strategic planning 0.365 0.779 0.266 2.289 0.028

Strategic competitive

positioning 0.250 0.633 0.135 2.333 0.040

ICT 0.633 0.743 0.035 1.348 0.006

Organizational learning 0.474 0.434 0.430 2.357 0.009

Dependent Variable: Aggregate means of organizational performance.


Source; Research data, 2014

From Table 4.6, the regression results reveal that strategic management drivers overall effect

on performance was statistically significant (overall p-value = 0.008). At the individual level,

all the strategic management drivers had positive and significant effect on organizational

performance as follows, CRM had positively influenced performance (β = 0.540 and p-value

= 0.037). Strategic planning also positively affected performance (β = 0.365, p-value =

0.028). Strategic competitive positioning had a positive effect on the performance (β = 0.250,

p-value = 0.040). ICT on the other hand had also positive impact on performance (β = 0.633,

p-value = 0.006) and organizational learning also positively impacted performance (β =

0.474, p-value = 0.009). In the table, the regression results shows that the regression of

strategic management drivers measures against the mean of hotel performance measures had

a beta term, β5 = 0.641. The regression results shows that hotel performance largely depends

on the strategic management drivers with 51.1 percent of hotel performance being explained

by strategic management drivers (R squared = 0.511). Arising from the research results in

Table 4.6, a simple regression equation that may be used to estimate performance of hotels in

Kenyan coast given its existing strategic management drivers can be stated as follows:

OP = 2.347 + 0.641CRM + 0.641SP + 0.641SCP +0.641ICT +0.641OL + ε

Where:

OP = Organizational performance

2.347 = the y- intercept constant (α = 2.347)


increase in use of strategic management drivers.

CRM= Customer Relationship Management.

SP= Strategic Planning.

SCP= Strategic competitive positioning

ICT= Information communication technology

OL= Organizational learning

ε= the slandered error term random- variation due to other unmeasured factors.

Regression results in Table 4.6 show that a unit change in CRM results in 38.1 percent

(β=0.381) change in organizational performance while a unit change in strategic planning



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112

results in 26.6 percent (β=0.266) change in organizational performance .On the other hand, a

unit change in strategic competitive positioning results in 13.5 percent (β=0.135) change in

hotel performance and ICT if implemented well will affect hotel performance by 51.1

percent. The study results presented in this chapter have utilized a variety of descriptive and

inferential statistics.

SUMMARY, CONCLUSION AND RECOMMENDATIONS

Summary and Key Findings

This study on the effect of strategic management drivers on organizational performance in

Kenyan coast had five specific objectives which were later developed into null hypotheses

and statistically tested using the Karl Pearson’s zero order. The discussions in the following

sections highlight the key findings of the study based on the hypotheses.

The first objective was to establish the effect of customer relationship management on

organizational performance. The study found out that CRM significantly and positively

affected organizational performance with 34.8 percent of the organizational performance (R

squared = 0.348) being explained by CRM.

The second objective was to determine the effect of strategic planning on performance of

hotels in Kenyan coast. The study found out that strategic planning significantly and

positively affected firm organizational performance with 36.4 percent of the hotel

performance (R squared = 0.364) being explained by strategic planning.

The third objective was to establish the effect of strategic competitive positioning (SCP) on

organizational performance in Kenya coast. The study found out that strategic competitive

positioning had significant and positive effect on organizational performance with 18.8

percent of the hotel performance (R squared = 0.188) being explained by strategic

competitive positioning.

The fourth objective was to establish the effect of ICT on organizational performance in

Kenyan coast. The study found out that ICT had significant and positive effect on

organizational performance with 26.4 percent of the hotel performance (R squared = 0.264)

being explained by ICT.

The fifth and final objective was to establish the effect of organizational learning(OL) on

organizational performance in Kenyan coast. The study found out that organizational learning

had a significant and positive effect on organizational performance with 34.2 percent of the

hotel performance (R squared = 0.342) being explained by ICT.

Managerial and theoretical implications

The results of this research paper should be of interest to managers of hotels that implement

strategic management drivers and to management consultants. The first implication of the

study is that managers should strive to enhance their strategic management drivers as this not

only improves their hotels’ ability to create superior customer value but also generally

enhances hotel performance. The study shows that strategic management drivers significantly

enhance both the qualitative and quantitative aspects of hotel performance which were

assessed through customer behavioural outcomes, market and financial outcomes

respectively. Finally, this study makes a useful contribution to the advancement of academic

knowledge on strategic management drivers from the context of sub-Saharan African setting

and particularly on hotels in Kenya. The extant literature decries the lack of scholarly



Vol.2, No.1, pp. 93-119, March 2014


113

contribution on strategic management drivers from Sub-Saharan Africa and on the hotel

sector. The study should encourage more scholarly output on strategic management drivers

and business strategy from Sub-Saharan Africa.

Conclusion

The study was based on the premise that strategic management drivers influence

organizational performance. The study results supported this premise in that strategic

management drivers (CRM, strategic planning, ICT, strategic competitive positioning and

organizational learning) were found to significantly and positively affect organizational

performance.

Recommendations

Based on the findings and conclusions of the study, the recommendations made were

That there is need for the hotels in Kenyan coast to employ strategic management drivers in

their operations as this improves their level of performance. Strategic management drivers

have been found by this study to have a great effect on improving organizational

performance.

Limitations of the study and Suggestions for Further Research

Although the study found out those strategic management drivers improves hotel

performance, the study did not come up with any optimum point at which the hotel should

employ them. The study also did not come up with a way of combining the various forms of

strategic management drivers’ mix. It is on the above bases that this study recommends

further studies to establish an optimum point or the strategic management drivers’ index for

the hotels.

Finally, the study relied on self reported data mainly from only one industry perspective

alone and used a single industry setting. Further research could seek to address this

limitation by use of multiple industries setting to conduct their studies and this would

enhance the validity and generalization of the research findings. Although this study has

mentioned some limitations, the findings are useful for managerial and theoretical

considerations. The study will assist intellectuals and be a reference for future studies and

practitioner undertakings on strategic management drivers and organizational performance

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